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. 2019 Dec 17;13:1313. doi: 10.3389/fnins.2019.01313

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Copyright © 2019 Santana, Cifre, de Santana and Montoya.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Local interpretable model-agnostic explanations (LIME) for the best TOPT model listing the 20 features that most contribute to the prediction of (a) a correctly predicted HC, (b) a correctly predicted CP, and (c) a wrongly predicted HC. The bars represent how much each feature (axis Y) added to the prediction in terms of probability. Green bars indicate that the feature adds positively, in direction to the target class, while the red bars indicate that the features are in resistance to the target class.